Ekaterini Vlachou

Cloud-based cyber-physical systems and quality of services

Purpose – The purpose of this paper is to review and explore the evolution, advances and future trends of cloud manufacturing, placing the focus on the quality of services. Moreover, moving toward the new trend of cyber-physical systems (CPS), a cloud-based cyber-physical system (CBCPS) is proposed combining the key enabling techniques of this decade, namely Internet of Things (IoT), cloud computing, Big Data analytics and CPS. Design/methodology/approach – First, an extensive review is made on cloud computing and its applications in manufacturing sectors, namely product development, manufacturing processes and manufacturing systems management. Second, a conceptual CBCPS which combines key enabling techniques including cloud computing, CPS and IoT is proposed. Finally, a review on the quality of the services (QoS) presented in the second step, along with the main security issues of cloud manufacturing, is conducted. Findings – The findings of this review indicate that the combination of the key enabling techniques presented in the CBCPS will lead to a new manufacturing paradigm capable of facing the new challenges and trends. The opportunities, as well as the challenges and barriers of the proposed framework are presented, concluding that the transition into this whole new era of networked computing and manufacturing has a valuable impact, but also generates several security and quality issues. Originality/value – The paper is the first to specifically study the QoS as a factor in the proposed manufacturing paradigm.

Cloud-Based Adaptive Shop-Floor Scheduling Considering Machine Tool Availability

Short-term scheduling belongs to the typical decision-making problems in manufacturing that continue to draw attention from industry and academia due to its inherent difficulties. The trend of mass customization and the increasing product variety generate further uncertainties and turbulences on modern shop-floors, thus, making scheduling a challenging daily problem. These challenges dictate the need for replacing rigid centralized scheduling tools with adaptive and robust scheduling solutions. The integration between ICT based decision support tools in manufacturing can be further enhanced to achieve shop-floor awareness and a common information flow, which is necessary to improve decision-making. Towards this objective, advanced monitoring techniques consisting of smart sensor networks and seamless communication procedures can provide the required awareness to decision making process. Further to that, Cloud, as an emerging enabling technology, can support the integration among multiple IT tools and provide ubiquitous access to data. Cloud-based and resource-aware scheduling tools are therefore considered as enablers for increasing the adaptability and agility of a manufacturing system. The proposed research work, presents a cloud-based framework consisting of a monitoring service and a short-term scheduling application that aims to generate and dispatch feasible and highly-productive schedules in a timely manner. The short-term scheduling application is enriched with data obtained by the monitoring service and generates resource-aware schedules by considering not only machine tools suitability but also their imminent status and availability. The scheduling application utilizes an intelligent search algorithm, which allows the generation of alternative schedules and their evaluation though a set of multiple conflicting criteria including among others cost, time and quality. The produced schedules are assessed using a set of performance indicators of makespan and resource utilization. The monitoring service gathers data from two data sources, namely a multi-sensory system and the machine tool operator. Through an information fusion procedure, the monitoring service provides to the scheduling application the machine tools status as well as the machine tools available time windows. The sensory system is deployed on five axes work-centers to monitor the axis and spindle drives in near real-time. The human operator reports to the monitoring system the status of the machine tool, the currently running task, and the cutting-tool availability through mobile devices on the shop-floor. The information fusion technique, consisting of the Analytic Hierarchy Process and the Dempster’s Shafer theory of evidence, processes these heterogeneous information sources and derives the status of the machine tool and future availability windows. The proposed framework is applied and validated in a real-life case study obtained from a high precision mold-making industry.Copyright

Linking Modular Product Structure to Suppliers’ Selection Through PLM Approach: A Frugal Innovation Perspective

To maintain market share rates, frugal innovation is a main solution for competitive enterprises to meet the customer’s needs in different regional markets. The co-evolution of product and production network aims to manage local production sites of the OEM and several collaborative relations between OEM and supplier companies for better management of the project resources in the regional market. Supplier selection and evaluation are among the main factors to be resolved at the earlier stage to guarantee successful results from any OEM-Supplier collaboration. This paper discusses the potential of using a modular-based approach as a kernel methodology to support the co-evolution of product structure and production network definition, especially in the case of supplier selection for frugal innovation perspective. The application of PLM approach to manage interconnected data describing the co-evolution of the product structure and production network is also discussed.

Integrated Production and Maintenance Scheduling Through Machine Monitoring and Augmented Reality: An Industry 4.0 Approach

Maintenance tasks are a frequent part of shop floor machines’ schedule, varying in complexity, and as a result in required time and effort, from simple cutting tool replacement to time consuming procedures. Nowadays, these procedures are usually called by the machine operator or shop floor technicians, based on their expertise or machine failures, commonly without flagging the shop floor scheduling. Newer approaches promote mobile devices and wearables as a mean of communication among the shop floor operators and other departments, to quickly notify for similar incidents. Shop floor scheduling is frequently highly influenced by maintenance tasks, thus the need to include them into the machine schedule has arisen. Moreover, production is highly disturbed by unexpected failures. As a result, the last few years through the industry 4.0 paradigm, production line machinery is more and more equipped with monitoring software, so as to flag the technicians before a maintenance task is required. Towards that end, an integrated system is developed, under the Industry 4.0 concept, consisted of a machine tool monitoring tool and an augmented reality mobile application, which are interfaced with a shop-floor scheduling tool. The mobile application allows the operator to monitor the status of the machine based on the data from the monitoring tool and decide on immediately calling AR remote maintenance or scheduling maintenance tasks for later. The application retrieves the machine schedule, providing the available windows for maintenance planning and also notifies the schedule for the added task. The application is tested on a CNC milling machine.

An approach for the modelling and quantification of PSS customisation

A Product–Service System (PSS) is a dynamic and multidimensional system that is comprised of products, services, a large network of stakeholders and all necessary supporting infrastructures, aiming towards becoming continuously competitive, satisfying customer needs and improving environmental aspects. The design of such a system and its evaluation throughout the lifecycle are challenging tasks owing to their inherent complexity, which becomes even greater when the aspect of customisation is considered. Nevertheless, the literature work regarding the customisation of PSS is scarce. Towards bridging this gap, the present work proposes a framework for PSS customisation, including the main steps that are required for a successful PSS customisation. For each step in the framework, which has been collected from the literature, PSS approaches have been provided, and could be used in the execution of each step. Next, the present study introduces a method for: (i) the modular representation of PSS based on vector analysis, and then (ii) the quantification of the PSS customisation degree.

Modularity as a support for frugal product and supplier network co-definition under regional market constraints: a mirroring hypothesis application

Creating new products or adapting existing ones to fit with specific customer requirements from regional as well as emerging markets is a challenging issue for competitive companies that work to maintain acceptable market share rates. Besides the importance of providing original solutions tailored to the target market characteristics, companies should consider their production strategy as a key factor for reaching frugality objectives under regional constraints. The co-evolution of product and production network aims to provide a concurrent design and management of product architecture, local production systems, and OEM–suppliers relationships. This paper proposes a modular-based approach as an application of the mirroring hypothesis for supporting the co-definition of product structure and supplier network. Supplier selection and evaluation method for frugal innovation perspective is proposed as a key part of the proposed approach and applied in an industrial use case for validation.